\Header{animals}{Attributes of Animals}
\keyword{datasets}{animals}
\begin{Description}\relax
This data set considers 6 binary attributes for 20 animals.\end{Description}
\begin{Usage}
\begin{verbatim}data(animals)\end{verbatim}
\end{Usage}
\begin{Format}\relax
A data frame with 20 observations on 6 variables:
\Tabular{rll}{
[ , 1] & war & warm-blooded \\{}
[ , 2] & fly & can fly \\{}
[ , 3] & ver & vertebrate \\{}
[ , 4] & end & endangered \\{}
[ , 5] & gro & live in groups \\{}
[ , 6] & hai & have hair \\
}
All variables are encoded as 1 = `no', 2 = `yes'.\end{Format}
\begin{Details}\relax
This dataset is useful for illustrating monothetic (only a single
variable is used for each split) hierarchical clustering.\end{Details}
\begin{Source}\relax
Leonard Kaufman and Peter J. Rousseeuw (1990):
\emph{Finding Groups in Data}
(pp 297ff).
New York: Wiley.\end{Source}
\begin{References}\relax
Anja Struyf, Mia Hubert \& Peter J. Rousseeuw (1996):
Clustering in an Object-Oriented Environment.
\emph{Journal of Statistical Software}, \bold{1}.
\url{http://www.stat.ucla.edu/journals/jss/}\end{References}
\begin{Examples}
\begin{ExampleCode}
data(animals)
apply(animals,2, table) # simple overview

ma <- mona(animals)
ma
## Plot similar to Figure 10 in Struyf et al (1996)
plot(ma)
\end{ExampleCode}
\end{Examples}

